Personalization is using AI to tailor what each person sees, such as videos, products or news, based on what they and similar people have liked before.
In plain words
Recommendation models learn from past behaviour: what you watched, clicked or bought, and what people with similar tastes chose. They score each item for how likely you are to like it and show the best ones. Services like YouTube and Google Play use this, and researchers have published dedicated deep learning models for it, such as DLRM.
A quick example
After you watch two cooking videos, the home page starts showing more recipes and a kitchen-knife review. The model has learned that people who watched those videos often enjoyed these too.
Where you'll meet it
- Video, music and shopping apps.
- News feeds, ads and search results.
Related
Sources
- DocsRecommendation systems overview, Google Machine Learning Education · read 29 Sept 2026
- PaperDeep Learning Recommendation Model for Personalization and Recommendation Systems, Naumov et al. (arXiv) · read 29 Sept 2026
Checked by WhatIsAI against the sources above · 29 Sept 2026. Spotted an error? Report it.